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Eligibility

Participants for training in Biostatistics should possess at least a Masters degree in Statistics, Biostatistics, Mathematics, Agricultural Statistics, or related discipline. A PhD will be an advantage. Participants must be proficient in Base module of SAS Software.

1. Introduction to New Drug Development Process (2 hours)

The purpose of this lecture is to familiarize the participants with new drug development process, Clinical Trials Phases (I, II, III, IIIa, IIIb, IV), and various terminology commonly used in the pharmaceutical and healthcare industry, such as NDA, BLA, Label, Patent Licensing, ICH, GCP, FDA, EMPEA, 21 CFR Part 11, Label Update, Ethical Committee, IRB, DSMB, ISE, ISS, SCE, SCS, Standard Operating Procedures (SOP), etc.

2. Clinical Trials Activities - Brief Details (2 hours)

This lecture will provide information on various activities in clinical trials, such as Protocol Development Process, Case Report Forms (CRFs), Statistical Analysis Plan, Clinical Data Management (CRF Annotation, data Entry, Data Edit checks, Tracking of queries and resolutions, Coding of Adverse Events and Concomitant Medications, Quality Assurance of Database, Database Clean-up, Database lock, Data transfer to sponsor, Database unlock and re-lock), Statistical Analysis & Reporting (Programming of Safety and Efficacy Tables, Listings, and Figures, Unblinding of Randomization Code, Integrated Analysis), Release of Clinical Trials Analysis Results, Medical Writing (Pre-Meeting NDA Briefing Package for submission to FDA, Clinical Study Report, Integrated Summary of Safety and Efficacy, Clinical Overview, Statistical Overview, Publishing of Documents in GlobDoc for Electronic Submission), Templates of Protocol, CRF, SAP, CSR, Project timelines and deliverables, etc.

3. Developments in NDA Submissions to FDA/Regulatory Authorities - Brief details (1 hour)

This lecture will apprise the participant on development in the documentation of New Drug Application (NDA) submitted to regulatory authority referring to a check list of items included in NDA submissions, On Paper Submissions, Electronic Submission (eNDA, eCTD), Common Technical Document (CTD), SAS Database as transport files, CDISC compliant SAS database, etc.

4. Biostatistics - Training (80 hours)

  • Protocol Development 
    • Efficacy endpoints definition 
    • Study design 
    • Sample size calculations 
    • Statistical methodology
    • Randomization procedure 
  • Statistical Analysis Procedure 
    • Statistical Analysis Plan 
    • Mock Safety and Efficacy Tables, Listings, and Figures (TLFs) 
    • Derived variables specification, visit windows algorithm 
    • Handling missing data
    • Interim Analysis 
    • Subpopulations definition and analysis 
    • Program inferential statistical tables 
    • Exploratory analysis - interactions, testing model assumptions 
    • Sensitivity analysis for robustness of study results (specially for dropouts) 
    • Ad hoc analysis to support marketing and publication
    • Common methods for analysis of clinical data with continuous, categorical, and time to event endpoints 
  • Validation of Tables, Listings and Figures 
    • Write independent SAS programs for validation 
    • Write validation documents 
  • Integrated Analysis 
  • Introduction to statistical software used in clinical trials data analysis
  • Mentoring: one-to-one meeting, evaluation, and guidance 

Training Plan

  • Two weeks intensive training 
  • Morning session: 
    • Lectures 
  • Afternoon session: 
    • Tutorials 
    • One-to-one meetings 
  • Each participant will program: 
    • 9 Standard Tables of Efficacy Inferential Tables 
    • 2 Listings 
    • 1 Graph 
  • Training on a real data of a clinical trial 
  • Training will be similar to an on-the-job training
  • Online guidance and tutoring for 3 months after training 
  • Award of Training Certificates 
  • Placement guidance 

 

List of Standard Tables, Listings, and Figures to be programmed

by Biostatistics Participants

  • Demographic and Baseline Characteristics 
  • Primary Efficacy Endpoint - Descriptive Statistics 
  • Secondary Endpoint - Descriptive Statistics 
  • Analysis of primary efficacy endpoints 
  • Analysis of secondary efficacy endpoints 
  • Kaplan Meier Analysis of Time to Event
  • Proportional Hazard Analysis 
  • Responder Analysis 
  • Pharmacokinetics Data Analysis 

Listings

  • Patient Demographics 
  • Efficacy Evaluations 

Figures

  • Response over time